BROCKVILLE, ON: JULY 01, 2013 -- Brockville's skyline raised a new Canadian flag to commemorate the birthplace of the flag, July 01, 2013. Former resident, John Ross Matheson, 95 years old, is considered by many as the father of our flag.

The quickened pace might come as a shock to you, in your life, because you just left August where the living is easy.

Economic activity in Canada reaches its peak every year in this month, as measured by the total value of all we produce. As a result, GDP in a typical September is 10% above its seasonal low in January.

This is startling volatility compared with what Statistics Canada reports in its seasonally adjusted data after removing the recurring seasonal peaks and valleys from the data. In those numbers a 1% monthly change would leave any economist’s mouth agape.

There are very good reasons why the country’s statistical overlords — of which I was one for many years — attempt to sterilize the affects of seasonality. If change was always explained away by the affects of the weather, then decision makers of all types, from investors to business leaders to statistical agencies, would never have even a modicum of certainty about the economy. And since there is no country where seasonality has a bigger affect than in Canada, there is no country where removing it is as important.

These efforts create two, almost contradictory, issues. There is the fairly cosmetic problem that most Canadians only get a statistical view of their economy, and it’s one that is far different from reality. The more troubling issue is that seasonal effects are so vast, and the removal so imperfect, that even the adjusted figures can often give us a distorted view of longer-term economic heath.

The seasonal reality

First off, here is a snapshot of what your economy really looks like.

In reality, Canadians produce more in September for several easily understood reasons. Summer vacations are over for most people, marking a return to work for those who take a holiday break in July and August (the full-time equivalent of nearly four million Canadians are on vacation in these two months). The school year throttles up for everything from kindergarten through university, involving millions of students, teachers and administrators. On the farm, harvesting is at its peak and processing those goods into the food chain is underway. And wherever work is done outdoors — a growing segment of our economy due to the boom in the resource and construction industries over the past decade — there is a rush to complete projects before the inevitable slowdown due to colder weather.

Economic activity begins to decelerate as the days get shorter and colder. This seasonal slowdown is gradual until the new year, with November and December receiving a big boost from consumer spending and travel related to Christmas. Once the new year begins, however, much of the economy goes into hibernation, with a typical drop of 5% in economic activity, led by a 20% freefall in retail sales.

The economy quickly expands with the arrival of spring as outdoor projects gear up, transportation links thaw out, auto and housing sales hit their seasonal peak in May, and farmers plant another crop. The summer doldrums soon arrive, and economic activity in July is even lower than in February as a result of vacations and the end of the K-12 school year. The seasonal cycle then repeats itself in September.

In practice, seasonal effects are hard to measure. There is no uniform seasonality in all industries, with their patterns varying widely from one to another. Retailing and construction see a seasonal low in January, but the cold weather that freezes spending in these industries is a boon to demand for electrical utilities. Auto sales peak in May, ahead of the summer driving season, but plunge in December when other retailers see peak sales.

Moreover, seasonal effects are not just weather-related, important as climate is for a country like Canada. Seasonality also includes what are called institutional effects, like Christmas or summer holidays. Even the varying number of days from month to month affects sales in most businesses.

Further complicating matters, seasonal patterns change over time. Christmas has become slightly less important to Canadian shoppers, partly because gift cards shifted spending from December into January and February. The recent adoption of Family Day in several provinces resulted in the loss of a full day’s business in February. New materials allow more construction work to continue in winter.

Only the major economic indicators like unemployment, retail sales and GDP are seasonally adjusted. Social and demographic data such as crime or births have seasonal patterns, but they are not seasonally adjusted. This is because it is more pressing for analysts to identify short-term shifts in the economy than it is to pinpoint social or demographic changes, which are driven mostly by long-term trends.

Dealing with seasonality

Because seasonal influences are ubiquitous in our economy, people have developed various methods to account for seasonality.

Businesses for centuries have created ways to deal with predictable, recurring seasonal fluctuations. For centuries, futures markets have allowed farmers to lock in their harvest price before they planted in the spring, while buyers in flour mills could plan on their purchase price. Prices in futures markets would then fluctuate over the summer as it became clear how good the crop would be.

The business community knows that comparing first-quarter sales at a retailer with the fourth quarter always results in a sharp drop in sales, due to Christmas. This gives a misleading reading of the underlying trend of business. To remove seasonal effects, almost all firms report their business performance by comparing with the same quarter a year earlier. However, this too has pitfalls. Were last year’s results distorted by delayed shipments by a supplier, or by Easter falling in March instead of April?

Statistical agencies like Statistics Canada also try to remove the impact of seasonal patterns. This involves complex estimates of recent seasonal patterns and adjusts for things like the number of days in a month. Saying housing starts rose 2% in January means the unadjusted data fell 18% instead of the usual 20%, something that the slightest change in weather can easily produce.

These complex estimates cannot remove all seasonal patterns from the data, as they are bedevilled by the same problems firms face in making their year-over-year comparisons. Seasonal adjustment only removes average weather, and as most people know from their everyday experience, weather in Canada rarely equals its long-term average. Partly, that is because North America, unlike Europe, has few geographic barriers to block air masses from moving rapidly north or south.

More importantly, seasonal patterns change over time. In the uproar over the July drop in employment in Canada this year, it went largely unnoticed that this was the fifth time in the last seven years that education jobs have disappeared in July, partly due to changing human resource strategies at school boards. It takes years for a new seasonal pattern to be incorporated into the calculation of seasonal factors, but only moments for the news media to become hysterical over the latest data point.

By itself, seasonally adjusted data from statistical agencies rarely reveals the underlying trend of the economy. This is partly because there is always some residual seasonality in the data. Since seasonal swings of 10% or more are routine, a small error in estimating seasonality can easily produce results in which residual seasonality swamps all other signals from the data.

The first task of analysts evaluating the latest data point is to try and remove the residual seasonal influences that remain in the data. The game then becomes sorting out the mix of other irregular factors unrelated to seasonality that buffet the economy, to boost the ‘signal’ of what the true underlying trend is relative to the ‘noise’ of events that aggravate the volatility of the economy.

A wide range of these irregular factors knock the economy around from month to month, reflecting everything from the timing of the latest blockbuster film/videogame/cellphone release to labour disputes. Another example of volatility is how the arrival of one ultra large oil tanker on the first day of a month instead of the last day of the previous month can shift $500-million of imports from one month to the other.

The essential point is that readers should be suspicious of any report claiming that the economy has changed drastically based on one report or datapoint. Most likely, you are really reading a weather report, thinly-disguised as financial news. Given the outsized importance of seasonality in the Canadian economy, people should be aware of this when listening to stories that breathlessly claim the latest numbers reveal a new emerging trend.

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